{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3d36ba1f-0b8d-4a0a-997a-d3d50864c4d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load up granular log file, calculate mean and variance for each\n",
    "import numpy as np\n",
    "\n",
    "def meanvar(filename):\n",
    "    bbox = []\n",
    "    segm = []\n",
    "    with open(filename) as f:\n",
    "        content = f.readlines()\n",
    "#     print(content[:4])\n",
    "    for l in content:\n",
    "        if l.startswith('bbox AP50'):\n",
    "            bbox.append(l)\n",
    "        if l.startswith('segm AP50'):\n",
    "            segm.append(l)\n",
    "#     print(bbox, segm)\n",
    "    bbox = np.asarray([float(x.strip()[len('bbox AP50 '):]) for x in bbox])\n",
    "    segm = np.asarray([float(x.strip()[len('segm AP50 '):]) for x in segm])\n",
    "    print(f' samples {len(bbox)}') #, bbox[:2], len(segm), segm[:2])\n",
    "#     print(f'bbox mean {bbox.mean()}, std {bbox.std()}')\n",
    "#     print(f'segm mean {segm.mean()}, std {segm.std()}')\n",
    "    return [bbox.mean(), bbox.std(), segm.mean(), segm.std()]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ac76b5d4-44f7-470f-8e1c-539afe9f0cfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#list dir for all the log files \n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def getkey_gtfix(f):\n",
    "    gt = f[f.find('gt10')+5:f.find('gt10')+6]\n",
    "    print(f'gt {gt}')\n",
    "    return int(gt)\n",
    "\n",
    "def getkey_pfix(f):\n",
    "    gt = f[f.find('gt')+2:f.find('gt')+4]\n",
    "    print(f'gt {gt}')\n",
    "    if gt == '5p':\n",
    "        return 5\n",
    "    return int(gt)\n",
    "\n",
    "def main(logdir, key_fn):\n",
    "    data = {}\n",
    "    fs = glob.glob(logdir + '/*')\n",
    "    for f in fs:\n",
    "        print(f'file {f}')\n",
    "        print(key_fn(f))\n",
    "        print(f[len(logdir)+1:])\n",
    "        data[key_fn(f)] = meanvar(f)\n",
    "    bm = {}\n",
    "    sm = {}\n",
    "    bmerr = {}\n",
    "    smerr = {}\n",
    "    for k, v in data.items():\n",
    "        bm[k] = v[0]\n",
    "        sm[k] = v[2]\n",
    "        bmerr[k] = v[1]\n",
    "        smerr[k] = v[3]\n",
    "    bm = {k: v for k, v in sorted(bm.items())}\n",
    "    bmerr = {k: v for k, v in sorted(bmerr.items())}\n",
    "    sm = {k: v for k, v in sorted(sm.items())}\n",
    "    smerr = {k: v for k, v in sorted(smerr.items())}\n",
    "#     print(f'bm {bm}\\nbmerr {bmerr} \\nsm {sm} \\nsmerr {smerr}')\n",
    "#     plt.plot(bm.keys(), bm.values())\n",
    "#     plt.show()\n",
    "#     plt.plot(sm.keys(), sm.values())\n",
    "#     plt.show()\n",
    "#     print(bm)\n",
    "    return bm, bmerr, sm, smerr\n",
    "\n",
    "def compare(log_act, log_def, key_fn, fixed_label, x_label):\n",
    "    bm_act, bmerr_act, sm_act, smerr_act = main(log_act, key_fn)\n",
    "    bm_def, bmerr_def, sm_def, smerr_def = main(log_def, key_fn)\n",
    "    \n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10,3), dpi=100)\n",
    "    ax1.set_title(f'bbox AP50, {fixed_label}')\n",
    "    ax1.set_xlabel(x_label)\n",
    "    ax1.set_ylabel('AP50')\n",
    "    ax1.errorbar(bm_act.keys(), bm_act.values(), yerr=bmerr_act.values(), label='active')\n",
    "    ax1.errorbar(bm_def.keys(), bm_def.values(), yerr=bmerr_def.values(), label='baseline')\n",
    "    ax1.legend(loc=\"upper left\")\n",
    "\n",
    "#     plt.show()\n",
    "    \n",
    "    ax2.set_title(f'segm AP50, {fixed_label}')\n",
    "    ax2.set_xlabel(x_label)\n",
    "    ax2.set_ylabel('AP50')\n",
    "    ax2.errorbar(sm_act.keys(), sm_act.values(), yerr=smerr_act.values(), label='active')\n",
    "    ax2.errorbar(sm_def.keys(), sm_def.values(), yerr=smerr_def.values(), label='baseline')\n",
    "    ax2.legend(loc=\"upper left\")\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e01f3e88-6b3c-4248-9428-fef94ac15f3c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "file /checkpoint/apratik/finals/logs/active1k_final/straightline_apt0_gt20p2fix_corlnn_granular.txt\n",
      "gt 20\n",
      "20\n",
      "straightline_apt0_gt20p2fix_corlnn_granular.txt\n",
      " samples 1317\n",
      "gt 20\n",
      "file /checkpoint/apratik/finals/logs/active1k_final/straightline_apt0_gt15p2fix_corlnn_granular.txt\n",
      "gt 15\n",
      "15\n",
      "straightline_apt0_gt15p2fix_corlnn_granular.txt\n",
      " samples 656\n",
      "gt 15\n",
      "file /checkpoint/apratik/finals/logs/active1k_final/straightline_apt0_gt25p2fix_corlnn_granular.txt\n",
      "gt 25\n",
      "25\n",
      "straightline_apt0_gt25p2fix_corlnn_granular.txt\n",
      " samples 768\n",
      "gt 25\n",
      "file /checkpoint/apratik/finals/logs/active1k_final/straightline_apt0_gt5p2fix_corlnn_granular.txt\n",
      "gt 5p\n",
      "5\n",
      "straightline_apt0_gt5p2fix_corlnn_granular.txt\n",
      " samples 735\n",
      "gt 5p\n",
      "file /checkpoint/apratik/finals/logs/active1k_final/straightline_apt0_gt10p2fix_corlnn_granular.txt\n",
      "gt 10\n",
      "10\n",
      "straightline_apt0_gt10p2fix_corlnn_granular.txt\n",
      " samples 695\n",
      "gt 10\n",
      "file /checkpoint/apratik/finals/logs/default1k_final_v2/default_apt0_gt15p2fix_corlnn_granular.txt\n",
      "gt 15\n",
      "15\n",
      "default_apt0_gt15p2fix_corlnn_granular.txt\n",
      " samples 2053\n",
      "gt 15\n",
      "file /checkpoint/apratik/finals/logs/default1k_final_v2/default_apt0_gt5p2fix_corlnn_granular.txt\n",
      "gt 5p\n",
      "5\n",
      "default_apt0_gt5p2fix_corlnn_granular.txt\n",
      " samples 955\n",
      "gt 5p\n",
      "file /checkpoint/apratik/finals/logs/default1k_final_v2/default_apt0_gt25p2fix_corlnn_granular.txt\n",
      "gt 25\n",
      "25\n",
      "default_apt0_gt25p2fix_corlnn_granular.txt\n",
      " samples 1603\n",
      "gt 25\n",
      "file /checkpoint/apratik/finals/logs/default1k_final_v2/default_apt0_gt10p2fix_corlnn_granular.txt\n",
      "gt 10\n",
      "10\n",
      "default_apt0_gt10p2fix_corlnn_granular.txt\n",
      " samples 1524\n",
      "gt 10\n",
      "file /checkpoint/apratik/finals/logs/default1k_final_v2/default_apt0_gt20p2fix_corlnn_granular.txt\n",
      "gt 20\n",
      "20\n",
      "default_apt0_gt20p2fix_corlnn_granular.txt\n",
      " samples 724\n",
      "gt 20\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare(\n",
    "    '/checkpoint/apratik/finals/logs/active1k_final', \n",
    "    '/checkpoint/apratik/finals/logs/default1k_final_v2',\n",
    "    getkey_pfix,\n",
    "    'fixed propagation length',\n",
    "    '#GT Frames',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d171dcb2-8a59-4427-ad9f-28102c051023",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "file /checkpoint/apratik/finals/logs/active1k_gtfix_final/straightline_apt0_gt10p6_h1nn_granular.txt\n",
      "gt 6\n",
      "6\n",
      "straightline_apt0_gt10p6_h1nn_granular.txt\n",
      " samples 912\n",
      "gt 6\n",
      "file /checkpoint/apratik/finals/logs/active1k_gtfix_final/straightline_apt0_gt10p2_h1nn_granular.txt\n",
      "gt 2\n",
      "2\n",
      "straightline_apt0_gt10p2_h1nn_granular.txt\n",
      " samples 946\n",
      "gt 2\n",
      "file /checkpoint/apratik/finals/logs/active1k_gtfix_final/straightline_apt0_gt10p4_h1nn_granular.txt\n",
      "gt 4\n",
      "4\n",
      "straightline_apt0_gt10p4_h1nn_granular.txt\n",
      " samples 573\n",
      "gt 4\n",
      "file /checkpoint/apratik/finals/logs/active1k_gtfix_final/straightline_apt0_gt10p8_h1nn_granular.txt\n",
      "gt 8\n",
      "8\n",
      "straightline_apt0_gt10p8_h1nn_granular.txt\n",
      " samples 669\n",
      "gt 8\n",
      "file /checkpoint/apratik/finals/logs/default1k_gtfix_final/default_apt0_gt10p4_h1nn_granular.txt\n",
      "gt 4\n",
      "4\n",
      "default_apt0_gt10p4_h1nn_granular.txt\n",
      " samples 1893\n",
      "gt 4\n",
      "file /checkpoint/apratik/finals/logs/default1k_gtfix_final/default_apt0_gt10p6_h1nn_granular.txt\n",
      "gt 6\n",
      "6\n",
      "default_apt0_gt10p6_h1nn_granular.txt\n",
      " samples 1329\n",
      "gt 6\n",
      "file /checkpoint/apratik/finals/logs/default1k_gtfix_final/default_apt0_gt10p2_h1nn_granular.txt\n",
      "gt 2\n",
      "2\n",
      "default_apt0_gt10p2_h1nn_granular.txt\n",
      " samples 1459\n",
      "gt 2\n",
      "file /checkpoint/apratik/finals/logs/default1k_gtfix_final/default_apt0_gt10p8_h1nn_granular.txt\n",
      "gt 8\n",
      "8\n",
      "default_apt0_gt10p8_h1nn_granular.txt\n",
      " samples 1360\n",
      "gt 8\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare(\n",
    "    '/checkpoint/apratik/finals/logs/active1k_gtfix_final', \n",
    "    '/checkpoint/apratik/finals/logs/default1k_gtfix_final',\n",
    "    getkey_gtfix,\n",
    "    'fixed #GT frames',\n",
    "    'Propagation length'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be531b88-c4dd-479f-a050-69f2f4f28fbf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0856d7d7-ef5c-4019-86d5-d321368a8c3e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "loco",
   "language": "python",
   "name": "loco"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
